ESS-Bilbao Initiative Workshop. Beam dynamics: Simulations of high power linacs

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    ESS-Bilbao Initiative Workshop. Beam dynamics: Simulations of high power linacs - Presentation Transcript

    1. ESS Workshop How Well Do Our Numerical Simulations Predict the Beam Performance in the Linacs We Build? J. Stovall April, 2009 Bilbao ESS2009 Bilbao CERN/TERA
    2. Are Accurate Simulations Important? •We rely on them initially to validate/certify the machine design •Linac •Verify the design details •Bracket allowable errors •Identify expected sources of beam loss •Developing commissioning strategies •Beam properties on target •Energy, emittance & halo at full current •The codes themselves must be “certified” at some level ESS2009 Bilbao CERN/TERA
    3. Codes Do a Very Good Job Qualitatively 25 DTL-CCL Transition CCL-SCL Transition 1 0 L in a c s , a ll e r r o r s Predicted beam loss in 20 + m is m a tc h SNS warm linac with Beam Loss (W) P m in errors 15 Pave Pm ax 10 5 0 0 20 40 60 80 100 120 140 160 180 200 W (M e V ) Measured activation in the SNS CCL Measured Residual activation @ 1ft after ~ 48h 1 W gives ~ 100 mRem/hr at 1 ft after ~ 12 hrs Galambos, SNS ESS2009 Bilbao CERN/TERA
    4. Simulation Codes Agree at Few % Level UNILAC RMS Beam Size SNS DTL-1 99% Emittance Profiles 4 Codes Profiles 5 Codes 0.40 0.38 0.36 3% εt 0.34 εn,99% (πcm-mrad) 0.32 0.30 0.28 0.26 0.24 0.22 0.20 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 β Groening, GSI ESS2009 Bilbao CERN/TERA
    5. Codes Differ in the Details Radial Distribution at Tank 1 Exit 6.0 10 8 5 4 3 1M particle 2 2 5.0 10 8 5 ParTrans 4 3 2 2 IMPACT 104.0 8 LINAC 5 4 3 2 2 PARMELA I (nAmp) 103.0 8 PARMILA 5 4 3 2 2 102.0 8 5 4 3 2 2 101.0 8 5 4 3 2 2 100.0 7 11% 5 4 3 2 2 10-1.0 0 1 2 3 4 5 6 7 8 Normalized Beam Radius (σ) ESS2009 Bilbao CERN/TERA
    6. Is This the Right Question? •Some put far too much emphasis on how well our codes predict beam behave •Machines are never built exactly like our computer models say they should be •There are always unknown errors introduced during fabrication & assembly •We never know the exact initial conditions •Beam or linac parameters •We can come close, and the codes will give a good indication of what the beam will look like •Equally important, however, is to to show how the beam will change with various machine parameters •Simulations can predict much more than the diagnostics can appreciate ESS2009 Bilbao CERN/TERA
    7. The Codes •Beam Optics codes like Trace3D •Transform envelope with analytical space charge •Do a very 1st order good job •Used as basis for most tuning algorithms •PIC Dynamics codes •Parmila, Tracewin, Linac, Dynamion •106 particles with 3-D space charge •Matrix based •Do a good job on core simulations •Agree at few% level •Integrating dynamics Codes •Impact, Track, Tstep (Parmela) •Can now integrate ~109 particles through field maps ESS2009 Bilbao CERN/TERA
    8. Code Limitations •The real problem is •An accurate 6-D description of the initial beam particle distribution •An accurate description of the fields •Magnets and their alignment can be accurately mapped •The axial rf field distribution in RFQ’s is not measurable •The rf field distribution in DTLs & CCLs are probably reasonably well known from cavity calculations and bead pulls •The rf field distribution in SC cavities at operating temperature is anyone’s guess •Rf phase & amplitude errors are transient ESS2009 Bilbao CERN/TERA
    9. Simulations Can Predict More than the Diagnostics Can Appreciate = 35 = 60 = 90 o o o Experiment Int / Int_max [%] 0–5 5 – 10 10 – 20 DYNAMION 20 – 40 40 -100 PARMILA UNILAC, Final Distributions (Horizontal) • core: good agreement (ex. 35°) TraceWin • 90°: \"wings\" seen in exp. & sims • deviations at lowest densities LORASR Groening, GSI ESS2009 Bilbao CERN/TERA
    10. One-to-One RFQ Simulation:~1 B Particles • Benefits of simulating a large number of particles: actual number if possible - Suppress noise from the PIC method: enough particles/cell - More detailed simulation: better characterization of the beam halo 10 10 10 8 1M 8 10M 8 100M 6 6 6 4 4 4 ∆W/W (%) ∆W/W (%) ∆W/W (%) 2 2 2 0 0 0 -2 -2 -2 -4 -4 -4 -6 -6 -6 -8 -8 -8 -10 -10 -10 -100 0 100 -100 0 100 -100 0 100 ∆φ (deg) ∆φ (deg) ∆φ (deg) Phase space plots for 865 M protons after 30 cells in the RFQ. Mustapha, ANL ESS2009 Bilbao CERN/TERA
    11. Even 1B Particles Yield a Poor Representation of the Details TRACK, 1B particle SNS measurement in Simulation of an RFQ MEBT Jeon, SNS Mustapha, ANL ESS2009 Bilbao CERN/TERA
    12. SNS MEBT “Round Beam” Study Jeon, SNS ESS2009 Bilbao CERN/TERA
    13. The Roll of Codes in Machine Tuning •Steering strategies, model-based vs. empirical • Matching strategies, model-based vs. empirical • Combined with beam measurements •profiles & halo •emittance •beam loss •longitudinal measurements •Code limitations •Diagnostics limitations •SNS has the most relevant experience ESS2009 Bilbao CERN/TERA
    14. Model-Based Tuning at SNS •The simulations do a good job on the core, but •The particles we are concerned with are in the halo; one part in 1E6 •We are unable to measure beam properties at that level •We are lacking input distributions for simulations anywhere near that level •We have pretty good results for model-based tuning, but of course that is exercising only the core •Particles destined to get lost don'care what the core is t doing ESS2009 Bilbao CERN/TERA
    15. SNS Warm-Linac Tuning •In practice we set the warm linac quads up to the design values •PMQs in the DTL •EMQs in the CCL •With these values, the measured Twiss parameters of the beam core are within ~ 10% of expected •This is about as good as any matching can do •Or as good as we believe the measurements •Then at high beam intensity we adjust quad strengths manually to reduce beam loss down the linac. •These adjustments are typically < 1% “tweaks” ESS2009 Bilbao CERN/TERA
    16. SC Linac & HEBT Tuning •In the superconducting linac we set up the quads to the design values • The laser profile measurements show that the beam is poorly matched but • They are too slow to be used in iteratively with quad adjustments •In the HEBT we typically see a large mismatch •It is easily corrected using a model based technique •But the resulting losses at ring injection are higher after matching •Since we inevitably run out of time we roll back to the unmatched setup •Beam loss is minimized manually – monkey tuning. ESS2009 Bilbao CERN/TERA
    17. Beam Tracking vs. Beam Dynamics Codes Beam optics codes Beam dynamics codes (example: Trace-3D) (example: TRACK, IMPACT) Matrix based, usually first order Particle tracking, all orders included Hard-edge field approximation 3D fields including realistic fringe fields Space charge forces approximated Solving Poisson equation at every step Actual particles distribution: core, halo … Beam envelopes and emittances Slower, Good for detailed studies Fast, Good for preliminary studies including errors and beam loss Simplex optimization: Limited number Larger scale optimization possible of fit parameters It is more appropriate to use beam dynamics codes for optimization: – More realistic representation of the beam especially for high-intensity and multiple charge state beams (3D external fields and accurate SC calculation). – Include quantities not available from beam optics codes: minimize beam halo formation and beam loss. – Now possible with faster PC’s and parallel computer clusters … Mustapha, ANL ESS2009 Bilbao CERN/TERA
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